This study constructs a macroeconometric model (MEM) for the Iranian economy using annual time series data for the period 1964-1992. The major contributions and innovations of this study, which advances previously developed models for the Iranian economy, fall into four categories.

First, this model represents the first attempt to incorporate the production structure of an input-output system into an econometric model for Iran. To achieve this, a conversion matrix, which translates the aggregate demand components into the sectoral value added, is incorporated. This procedure captures the production interdependencies among inter-related sectors, as suggested by many leading modelbuilders such as Klein (1983) and Bodkin (1976).

Second, the estimated behavioural equations have been validated by a battery of parametric and diagnostic tests prior to the use of this model for any policy analysis. These diagnostic tests have been undertaken to check for various possible violations of the classical linear regression model.

Third, in this study time series properties of the data have been determined to avoid spurious regressions and/or inconsistent estimators. Almost all equations in the production side of the model use stationary data. On the demand side and for the monetary sector of the model, most of the equations have been balanced by equalising the order of integration of dependent and independent variables.

Fourth, most of the preceding model-builders for Iran used the two-stage least squares (2SLS) method to estimate a simultaneous equation system indiscriminately, but in this study the Hausman (1976) test has been utilised to determine the estimation method. If the simultaneity problem exists, the 2SLS method is used, but if not, OLS estimators are used.

The specification of the equations in this model is based on several sources, viz. macroeconomic theory, MEMs in other countries particularly in developing countries and the previous MEMs for Iran. In addition, the specification of the behavioural equations has been modified, where necessary, to capture specific institutional and structural features of the Iranian economy. Furthermore, in this model, there are some behavioural equations which have not been specified in previous MEMs for Iran, such as the equation for the black market exchange rate.

This model consists of 38 behavioural equations and 11 accounting identities. Most of the equations have been estimated on constant price (1982) data. The reliability of the complete model as a system has been tested using three evaluation criteria, viz. dynamic tracking performance, sensitivity and dynamic response. The dynamic tracking performance of the full model over the simulation period is both satisfactory and stable. Intercept impulse dummy variables are used extensively to capture a few outliers in each equation that occur as a result of the Iran-Iraq war, volatile oil exports, the Islamic revolution, and frequent data revisions by statistical centres.

Five counterfactual simulations are used to provide important policy recommendations in the context of Iranian policy making. The five simulation experiments during the period 1983-1992 show what would have happened to the endogenous variables over time, ceteris paribus, if one (or a combination of two) exogenous variable(s) had been subjected to an unsustained shock in the initial year of the simulations. These unsustained shocks pertain to a 100 billion rial increase in the following variables: government current expenditure; government capital expenditure; oil exports; government current expenditure and oil exports; government capital expenditure and oil exports.

The use of these "what if exercises deepens the understanding of the economic inter-dependencies among various macroeconomic variables. This study analyses the effect of the above-mentioned unsustained shocks on macroeconomic variables such as aggregate demand, sectoral value added, investment, consumption, the black market exchange rate, inflation, and employment over time. Most of the simulation results, expressed in terms of the percentage deviation from the control solution, are not counter-intuitive and capture the intrinsic structure of the Iranian economy. For example, Simulation 1, an increase in government current expenditure, financed by borrowing from the Central Bank, induces inflation, with a detrimental impact in the form of a rise in the black market exchange rate. The pursuit of this policy mainly increases value added in those service sectors which are likely to be associated with rent-seeking activities.

This study also employs several econometric methods, such as cointegration, causality and superexogeneity, to shed additional light on the fiscal and monetary policies of the Iranian government. The analysis also shows the robustness of the policy simulation results obtained using the Iranian macroeconometric model developed in this study, as the policy conclusions are not subject to reversals when different analytical techniques are applied.